2026-02-21 23:02:20
Welcome to the Saturday PRO edition of How They Make Money.
Over 290,000 subscribers turn to us for business and investment insights.
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📊 Monthly reports: 200+ companies visualized.
📩 Tuesday articles: Exclusive deep dives and insights.
📚 Access to our archive: Hundreds of business breakdowns.
📩 Saturday PRO reports: Timely insights on the latest earnings.
Today at a glance:
🛒 Walmart: E-Commerce Leads the Way
🛩️ Airbus: Engine Dispute Dents Outlook
⚙️ Analog Devices: Industrial Power Ahead
🏝️ Booking: Stacking Savings
💡 Cadence: AI Amplifies the Backlog
💼 Moody’s: AI Resilience
🥡 DoorDash: Local Commerce OS
🎤 Live Nation: A $25 Billion Encore
🌎 Global Payments: Pure-Play Pivot
🛵 Grab: Critical Proof Point
💻 Lenovo: AI Boom Meets Memory Crunch
🎨 Figma: AI Fears Fade For Now
💳 Klarna: Banking Pivot
📦 Etsy: Pure-Play Pivot
🛍️ Global-e: Scaling Through Intelligence
Walmart just reported its January quarter (Q4 FY26), and revenue grew 6% Y/Y to $190.7 billion ($2.4 billion beat). Adjusted EPS narrowly topped expectations, marking a resilient holiday season despite a compressed shopping window.
Walmart US comps rose 4.6%, matching consensus, driven by a 2.6% increase in transactions. International sales were a standout, climbing 11.5% to $35.9 billion, led by strength in China, Mexico (Walmex), and India (Flipkart).
The steady shift toward digital continued:
E-commerce momentum: Global e-commerce sales grew 24%, now representing 23% of total revenue. In the US, online sales jumped 27%, fueled by store-fulfilled delivery and a growing marketplace.
Profit diversification: High-margin streams (advertising and membership) now account for nearly one-third of total operating income. Global advertising grew 37% (bolstered by VIZIO), while membership revenue surged over 15%.
AI integration: The AI shopping assistant, Sparky, is showing early success. Customers using the tool have an average order value 35% higher than those who do not.
The Walmart US boss, John Furner, officially took over as CEO on February 1, 2026. Furner inherits a company with a healthy balance sheet, nearly $15 billion in free cash flow in FY26, and a massive new $30 billion share buyback authorization.
Inventory management remains a major win, with levels growing at just half the rate of sales growth, thanks to automation in 60% of US stores and 50% of fulfillment centers. This efficiency helped adjusted operating income grow 10.5%, significantly outpacing sales growth.
Despite the beat, shares saw some volatility due to a cautious FY27 outlook that missed analyst targets:
Sales growth: 3.5%–4.5% (vs. 5% consensus).
Adjusted EPS: $2.75–$2.85 (vs. $2.97 consensus).
Management cited an unpredictable macro environment, noting a widening spending gap between high-income households (earning over $100k) and stretched low-income consumers. While Walmart continues to gain share across all cohorts, it is bracing for potential headwinds from tariff-related cost pressures and normalized pricing.
Airbus closed FY25 with a mixed quarter, beating on the bottom line but missing on revenue and delivering a disappointing outlook.
Q4 revenue rose 5% Y/Y to €26.0 billion (€0.8 billion miss), while GAAP EPS was €3.27 (€0.50 beat). For the full year, the company saw revenue rise 6% Y/Y to €73.4 billion and posted a record Adjusted EBIT of €7.1 billion. Airbus delivered 793 commercial aircraft in FY25, backed by a backlog of 8,754 jets.
However, shares tumbled following an unusually public and combative rebuke of engine supplier Pratt & Whitney (an RTX subsidiary). CEO Guillaume Faury explicitly accused Pratt of failing to meet its contractual commitments for engine deliveries, prioritizing the maintenance of existing airline fleets over supplying new jets. Airbus announced it has formally triggered a dispute clause in its contract to seek compensation for lost business.
As a direct result of the engine shortage, Airbus significantly slashed its 2026 production guidance. The company now expects to deliver roughly 870 commercial aircraft in 2026 (well below the Wall Street consensus of 900+ jets) and generate an Adjusted EBIT of around €7.5 billion (missing the €8.2 billion expectation). The long-held goal of producing 75 A320s per month has been delayed yet again, now targeted for the end of 2027.
2026-02-20 21:02:48
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AI agents threaten to compress white-collar workflows, and markets have responded by repricing the entire sector. Over the past five years, the WisdomTree Cloud Computing ETF (WCLD) was cut in half, while the Nasdaq-100 (QQQ) has nearly doubled. Since our breakdown of the SaaSpocalypse last month, software stocks have dropped another 10%.
When narratives shift, markets rarely discriminate.
But look closer. A dispersion is emerging between those who sell human productivity and those who capture the rise in workloads.
Investors have questioned everything from seat-based pricing to enterprise IT budgets. Some predict agentic disintermediation on the horizon, with near-term earnings merely a distraction and terminal values revised toward zero.
The comparison to the printed press in the 2000s is common. But that analogy confuses disruption with extinction. The New York Times (NYT), once cited as a casualty of the Internet, is up nearly 6x over the past decade and has doubled the returns of the S&P 500.
Markets tend to extrapolate the present trend, bearish or bullish. But software is not a monolith.
The repricing underway is far more selective than it appears at first.
For years, software was treated as one category:
Recurring revenue.
High gross margins.
Scalable business models.
Favoring growth over profitability.
Whether it was CRM or cybersecurity, most companies benefited from the same secular tailwinds: cloud migration, digital transformation, and expanding enterprise IT budgets.
AI is forcing a more nuanced distinction.
Some software businesses scale primarily with headcount. Revenue grows as customers hire employees and provision more seats. When hiring slows or when automation reduces the need for certain roles, that growth engine weakens.
Others scale with infrastructure usage. Their revenue increases as compute workloads rise, traffic expands, systems grow more complex, and security risks multiply. AI does not compress those forces. It intensifies them.
The distinction matters because these two models respond differently to AI.
Application software is tied to labor intensity.
Infrastructure software is tied to computational intensity.
As AI adoption increases, those forces move in opposite directions. Application software is a tax on labor. Infrastructure software is a tax on compute.
Seat-based pricing may face pressure as workflows become more automated. In contrast, software linked to usage, traffic, and system complexity can expand alongside AI-driven workloads.
If AI increases traffic and system complexity, it also increases risk.
Every new API endpoint, cloud workload, or AI-powered workflow expands the potential attack surface. As enterprises embed AI into products and internal operations, the need for visibility and protection grows alongside it.
Palo Alto Networks (PANW) remains the largest ‘pure-play’ cybersecurity company today. Its software helps organizations secure networks, cloud environments, and endpoints across increasingly distributed systems.
Security budgets tend to behave differently from productivity budgets. Companies may slow hiring or delay software upgrades, but they rarely reduce protection when systems become more complex.
The most recent quarter reinforced this dynamic. PANW just reported Q2 FY26 results (January quarter). Revenue grew 15% to $2.6 billion, as enterprises continued consolidating vendors and expanding their security footprint.
The company has steadily improved its operating margin over the past five years, reaching a new high of 14% in the past 12 months (15% in Q2).
The core Next-Generation Security (NGS) Annual Recurring Revenue (ARR) expanded 33% to $6.3 billion, while the RPO backlog rose 23% Y/Y to $16.0 billion. For perspective, the NGS business is larger and growing faster than CrowdStrike’s entire ARR.
Management noted that 110 customers adopted multiple Palo Alto products rather than a single standalone tool. It favors unified platforms, specifically Strata (Network Security), Prisma (Cloud Security), and Cortex (Security Operations/AI-driven SOC)
This shift is increasingly driven by AI, as customers look to consolidate their security stacks to defend against more sophisticated, autonomous threats.
The quarter was defined by aggressive M&A activity aimed at rounding out the ecosystem:
Identity & observability: The company recently closed its $25 billion acquisition of CyberArk and its $3.3 billion deal for Chronosphere. These additions are expected to be the primary growth engines for the remainder of the fiscal year.
Agentic AI: Palo Alto announced its intent to acquire Koi, an Israeli startup focused on agentic endpoint security. The goal is to secure autonomous AI agents and scripts that often operate outside traditional security visibility.
Product momentum: Prisma AIRS (AI Security) tripled its customer count to over 100 in just a few quarters, while the SASE business surpassed $1.5 billion in ARR.
Palo Alto just raised its revenue and ARR outlook substantially, but the increase is largely attributable to two recent acquisitions. A lowered EPS guidance reflected higher memory and storage costs, as well as share dilution from the massive CyberArk transaction. The stock fell after earnings as investors weighed the revenue surge against the near-term margin pressure and acquisition costs.
The company reiterated its long-term FY30 goal of $20 billion in NGS ARR and its FY28 target of 40%+ free cash flow margins (from mid-30s today).
If AI agents become the new users of the web, they still rely on the same foundational layer, the network.
Cloudflare (NET) operates at that layer. It routes traffic, secures endpoints, mitigates attacks, and increasingly runs compute at the edge. Unlike application software that scales with employees, network software scales with requests and workloads.
AI increases both.
As companies deploy AI features, API calls multiply. Systems become more distributed. Traffic patterns grow less predictable. Security risks expand. Each of those forces drives demand for routing, protection, and edge execution.
This is why Cloudflare’s growth trajectory has diverged from many application software businesses. Its revenue is tied less to hiring cycles and more to digital activity itself. The company’s revenue growth re-accelerated to its fastest pace in nearly three years.
In a world of agentic workflows and machine-to-machine communication, the network layer becomes more central, not less.
If the network layer moves traffic, the observability layer explains what happens after that traffic arrives.
Datadog (DDOG) provides monitoring across logs, metrics, traces, and increasingly AI workloads themselves. In modern cloud architectures, where applications are distributed across services and regions, observability is mission-critical.
AI adds another layer of complexity. Models generate new workloads, services interact in more dynamic ways, and latency or performance issues carry greater consequences. As systems grow more intricate, visibility becomes more valuable.
The largest operating expense for most software businesses is sales & marketing (S&M). In contrast, Datadog is a typical case of product-led growth. Most of the gross profit is plowed back into R&D expenses.
Unlike seat-based application software, observability tools scale with infrastructure usage. More services, more traffic, and more compute translate into greater monitoring demand. This explains why Datadog has reported a steady increase in multi-product adoption, with 18% of its customers using over 8 products.
This dynamic helps explain why certain infrastructure-oriented software companies are seeing stabilization or re-acceleration even as parts of the broader SaaS universe remain under pressure.
As Datadog CEO Olivier Pomel noted last week, AI-native customers are “growing significantly faster than the rest of the business” as their workloads move into production and expand across users and tokens.
The keyword is production. As experimental AI deployments scale into real systems, monitoring demand scales with them.
If the divide between application and infrastructure software continues to widen, it should show up in the numbers.
Watch for:
Usage-based revenue trends: Companies tied to compute, traffic, and cloud workloads should see stabilization or acceleration before seat-based vendors.
Net retention dynamics: Infrastructure software should benefit from expanding workloads even if hiring remains muted.
Security and observability budgets: As AI adoption grows, spending on protection and monitoring should prove more resilient than spending on productivity tools.
Cloud CapEx and workload growth: If hyperscaler investment remains elevated, infrastructure-linked software stands to benefit.
New business models: Monitor shifts toward usage-based services or flat-tier subscriptions based on the service delivered.
The broader narrative may still treat software as one category. But the economics underneath are diverging.
And markets eventually reprice divergence.
That’s it for today!
Stay healthy and invest on!
Thanks to Fiscal.ai for being our official data partner. Create your own charts and pull key metrics from 50,000+ companies directly on Fiscal.ai. Start an account for free and save 15% on paid plans with this link.
Disclosure: I own PANW, DDOG, and NET in App Economy Portfolio. I share my ratings (BUY, SELL, or HOLD) with members.
Author's Note (Bertrand here 👋🏼): The views and opinions expressed in this newsletter are solely my own and should not be considered financial advice or any other organization's views.
2026-02-18 09:36:04
Welcome to the Premium edition of How They Make Money.
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Every quarter, funds managing over $100 million must disclose their portfolios, offering a rare glimpse into the minds of elite investors.
The latest 13F filings capture trades from October 1 to December 31.
Q4 was defined by an AI infrastructure arms race and massive CapEx commitments from Big Tech. The market has increasingly concentrated in a handful of dominant players as rate-cut expectations shifted into 2026.
Against that backdrop, super investors repositioned into year-end, just before software sentiment began to crack in early 2026.
Some doubled down on winners, others quietly rotated.
Let’s see where the smart money leaned.
Today at a glance:
Hedge funds’ strategies.
Top buys and top holdings in Q4.
A surprisingly popular buy.
Implications for individual investors.
Before we dive into 13Fs, a quick reminder: blindly copying hedge fund trades is a terrible strategy.
Investing is like shooting 3-pointers. Even Steph Curry, the greatest shooter ever, misses more than half the time. There are no sure bets, even for the pros.
Your behavior matters more than your portfolio. As Peter Lynch said, “Know what you own and why you own it.”
Conviction is what helps you hold through volatility. And conviction comes from doing your own work, not borrowing someone else’s.
As Ian Cassel puts it:
“You can borrow someone else’s stock ideas but you can’t borrow their conviction. […] Do the work so you know when to sell. Do the work so you can hold. Do the work so you can stand alone.”
Some limitations of 13F filings:
Omit short positions and cash reserves.
Offer a partial view, leaving out smaller funds.
Exclude non-US equities, bonds, and commodities.
Can be dated, given their submission 45 days after the quarter.
With all this said, let’s see what top funds were buying and holding in Q4.
Hedge funds are financial powerhouses known for flexible, aggressive strategies designed to beat the market.
Here’s what typically shapes their moves:
Market conditions: Long in bull markets, defensive in bear markets.
Sector trends: Shifts in regulation or consumer behavior steer capital.
Fundamentals: Strong earnings, free cash flow, and leadership matter.
Macro factors: Rates, inflation, and geopolitics influence positioning.
Quant models: Some lean on proprietary algorithms to find an edge.
Risk management: Diversification, hedging, and position sizing.
Investor sentiment: Fear and greed create mispriced opportunities.
Still, it doesn’t always work out.
The Global X Guru ETF (GURU), built to track top hedge fund holdings, has underperformed the S&P 500 since its inception in 2012, even before fees.
And those fees matter. The classic “2 and 20” model (2% of assets + 20% of gains) can significantly reduce returns. It's no wonder that many individual investors are opting for simpler, lower-cost strategies.
Our partners at Fiscal.ai gather the data on Super Investors and visualize their portfolio for you. Pick your favorite investors and see how their holdings have evolved.
In early 2020, just before the COVID market turmoil, I curated a list of 20 top-performing hedge funds using TipRanks data. The selection focused on alpha relative to the S&P 500, and I also included a few funds frequently featured in my social feeds and podcast rotation. It’s not perfect, but it remains a solid directional filter.
The 10 stocks below represent half of the top holdings listed:
🤖 AI infrastructure: META, NVDA, TSM, GEV.
☁️ Hyperscalers: AMZN, MSFT, GOOG.
📦 Global commerce: SHOP, MELI, SE, V.
Amazon remains by far the most widely held stock at the top of these portfolios, appearing in 12 of the 20 funds. Also, note that Apple is entirely absent despite being the second-largest company by market cap globally. You also won’t find Tesla here.
This list of holdings doesn’t change much from one quarter to the next, so let’s turn to the more actionable insights with the new movements in Q4.
2026-02-14 23:02:19
Welcome to the Saturday PRO edition of How They Make Money.
Over 290,000 subscribers turn to us for business and investment insights.
In case you missed it:
📊 Monthly reports: 200+ companies visualized.
📩 Tuesday articles: Exclusive deep dives and insights.
📚 Access to our archive: Hundreds of business breakdowns.
📩 Saturday PRO reports: Timely insights on the latest earnings.
Today at a glance:
🌐 Cisco: AI Boom & Margin Squeeze
🛍️ Shopify: The Cost of Agentic Growth
⚙️ Applied Materials: AI Ramp Begins
🧬 AstraZeneca: Oncology Drives the Beat
🥤 Coca-Cola: Rare Miss & A New Boss
🍟 McDonald’s: The Grinch Wins Christmas
📶 T-Mobile US: Guidance to the Rescue
🌐 Arista Networks: AI Validation
📱 AppLovin: The Great Disconnect
🎮 NetEase: Hitting the Brakes
🪶 Robinhood: The Crypto Fade
🛖 Airbnb: Growth Acceleration
✈️ Expedia: B2B Powerhouse
🏨 Marriott: Credit Card Kicker
🏨 Hilton: Guidance Gloom
👜 Hermès: The Untouchable
💄 L'Oréal: Luxe Drag But Derma Shine
🧣 Kering: Not as Bad as Feared
🏎️ Ferrari: Luxury of Less
🚙 Ford: Tariff Shock
☁️ Cloudflare: The Agentic Internet
🐶 Datadog: Best in Show
📈 Coinbase: Cyclical Reset
💳 Adyen: Growth Reset
💳 Fiserv: Hard Reset
🌭 Kraft Heinz: The Great Pause
🍔 RBI: Burger King Remodels Slow
💬 Twilio: AI Infrastructure Pivot
🍞 Toast: Profitable Pivot
🏠 Zillow: Rentals Boom But Profit Gloom
👑 DraftKings: Prediction Gamble
📌 Pinterest: Exogenous Shock
📢 HubSpot: Agentic Pivot Pays Off
🚘 Lyft: Headline Shock
🏴 Klaviyo: Autonomous Growth
📆 Monday.com: Guidance Trap
Cisco’s Q2 FY26 (January quarter) revenue accelerated to 10% Y/Y growth, hitting $15.3 billion ($230 million beat), while adjusted EPS came in at $1.04 ($0.02 beat).
The AI infrastructure momentum continued. AI orders from hyperscalers jumped to $2.1 billion in the quarter (up from $1.3 billion in Q1). Consequently, management raised its FY26 AI orders outlook to exceed $5 billion, driven by demand for its Silicon One chips and 800G optical pluggables.
Networking revenue surged 21% Y/Y, fueled by the hyperscaler spend and a campus refresh cycle. However, Security revenue declined 4%, continuing to lag as the portfolio transitions and integrates Splunk (acquired in March 2024).
Despite the top-line beat and accelerating AI story, shares fell post-earnings due to a disappointing margin outlook. Management guided Q3 adjusted gross margins to ~66% (well below the 68.2% consensus), citing surging memory chip prices that are inflating costs faster than Cisco can raise prices.
Cisco raised its full-year FY26 guidance again, now forecasting revenue of $61.2–$61.7 billion (up from $60.2–$61.0 billion). The company also raised its quarterly dividend to $0.42 per share. While the AI growth thesis is playing out faster than expected, investors are now grappling with the near-term profitability tax of that growth.
Shopify closed FY25 with a high-octane quarter that highlighted a deepening tug-of-war between growth and profitability.
Q4 revenue surged 31% Y/Y to $3.7 billion ($80 million beat), and Gross Merchandise Volume (GMV) climbed 31% to $124 billion. For the full-year, revenue rose 30% Y/Y to $11.6 billion. This marked the highest annual revenue growth since the COVID boom of 2021.
The stock plunged despite the top-line beat and the authorization of a new $2 billion share buyback. The culprit was the bottom line. Adjusted EPS of $0.48 slightly missed the $0.51 consensus, and management guided for Q1 Free Cash Flow margins to dip into the “low-to-mid teens” (down from 19% in Q4) as they aggressively ramp up spending on AI. Sounds familiar?
The company is betting heavily on the Agentic Internet, launching the Universal Commerce Protocol (UCP) in collaboration with Google to allow AI agents to shop on behalf of consumers. While management argued that “no one is better positioned” for this shift, investors are punishing the immediate margin compression required to build this infrastructure.
On the bright side, the core business is firing on all cylinders. B2B GMV exploded 84% Y/Y, International revenue grew 36%, and the company guided for Q1 revenue growth in the “low-thirties”—significantly ahead of the 25% consensus.
2026-02-13 21:03:06
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The company proved it can grow at a slower pace and still earn more. The market responded with shares jumping nearly 20% after record margins.
At the same time, management is repositioning Spotify as the infrastructure layer of the music industry and pitching an agentic media vision built around discovery and personalization.
Let’s dig in.
Spotify is accelerating in ways that surprised even its own leadership.
Monthly Active Users (MAUs): 751 million (+11% Y/Y). The company added a record 38 million net new users in Q4 alone, beating its own guidance by 6 million.
Premium Subscribers: 290 million (+10% Y/Y).
ARPU (Average Revenue Per User): €4.70, up 2% Y/Y in constant currency, benefiting from recent price hikes.
Revenue growth: +7% Y/Y to €4.5 billion (€10 million beat). Note that the company reports in euros and faced currency headwinds. Growth was +13% Y/Y in constant currency.
Gross margin: Expanded again to a record 33.1%, primarily thanks to an improvement in ad-supported gross margin, notably from podcasts.
Operating margin: 15% (a massive jump from 11% million a year ago).
Free cash flow: €834 million for the quarter and €2.9 billion for FY25.
Financially, the story has shifted from growth at all costs to margin expansion and shareholder returns. With €9.5 billion in cash and short-term investments, the company repurchased $433 million of its own shares during the quarter.
Management credited two major factors for the upbeat quarter:
The Wrapped effect: 2025 was the biggest Wrapped campaign ever. Over 300 million users engaged with their year-end recaps, driving the highest single day of subscriber sign-ups in the company’s history.
Product expansion: The rollout of audiobooks in more European markets and the beta launch of music videos in the US and Canada helped deepen user engagement.
This was Spotify founder Daniel Ek’s final quarter as CEO. Taking a page from the Netflix playbook, he passed the baton to two co-CEOs: Gustav Söderström (formerly Chief Product & Technology Officer) and Alex Norström (formerly Chief Business Officer).
Ek laid out a three-part framework for Spotify up to this point:
The intersection strategy: Spotify wins by solving problems at the intersection of consumers and creators. If a feature helps both, it’s a green light.
The R&D arm of music: Ek doesn’t see Spotify as a distributor but as the technology infrastructure for the music industry.
Ubiquity over control: Spotify works on over 2,000 devices from 200 brands. They chose to be everywhere rather than building a walled garden, which is why they believe they’re winning the “car and home” battle against Apple and Google.
The Ad-Supported segment remained the clear low-light. Ad revenue grew only 4% Y/Y in constant currency (it declined 4% Y/Y on a reported basis), continuing a trend of soft monetization that stands in stark contrast to the subscription side of the house.
Despite a massive base of 476 million ad-supported MAUs (up 12% Y/Y), Spotify still struggles to translate eyeballs into dollars as efficiently as Big Tech. Management has previously signaled that 2025 was a transition year for ads, but with growth not expected to truly accelerate until the second half of 2026, this segment acts as a persistent drag on the overall growth story.
The real insight, however, is the gross margin expansion within the ad tier, which hit record levels primarily due to “content cost favorability” in podcasting. For years, podcasts were a massive cash burn. They are now finally becoming margin-accretive. By pivoting from expensive exclusive deals to a broader marketplace model, Spotify is proving it can make the ad business profitable even if it isn’t yet a high-growth engine.
The strategic bet is that Spotify can eventually unlock the kind of high-ARPU targeted advertising that powers Meta and YouTube. That outcome is far from guaranteed.
Audio has structural limits. Unlike visual feeds, ads cannot be scrolled past. Ad load is constrained. That likely caps ARPU below video and social platforms.
There is also a data quality gap. Spotify understands moods and habits, but it lacks the high-intent commercial signals that make Google and Meta so effective for performance marketing. Mood data supports branding. It does not drive clicks.
Spotify does not see AI as a threat. It sees it as leverage.
Co-CEO Gustav Söderström argues that disruption isn’t caused by technology alone. It’s caused by new business models enabled by that technology. Spotify’s bet is that AI won’t eliminate aggregators. It will make them more important.
If AI makes it easier to create music, the world will drown in supply. When supply becomes infinite, discovery becomes scarce. And discovery is Spotify’s core product.
Already, 90 million users engage with the AI DJ. The new Prompted Playlist feature lets users “write their own algorithm,” turning Spotify into an interactive recommendation engine rather than a passive library. Users can also exclude suggested songs, like creating new rules for an LLM.
This is the key. AI threatens creators more than platforms. The more content exists, the more valuable the filter becomes.
Spotify is positioning itself as that filter. Management called it an “agentic media platform” that translates language, mood, and context into taste.
If that works, AI doesn’t compress Spotify’s moat. It widens it.
Spotify does not own its content. Labels capture close to 70% of revenue. The catalog is largely the same across Apple, YouTube, and Amazon.
So where is the edge?
It lives in experience, data, and scale:
Personalization at depth: Spotify is building a dataset that connects language to taste at global scale. “Workout music” or “sad songs” are not objective categories. They are subjective signals defined by hundreds of millions of users every day. That feedback loop trains recommendation systems that are difficult to replicate without similar scale and engagement.
Network gravity: With 751 million monthly users, Spotify is the default destination for audio. Artists and podcasters launch where distribution is largest. Innovation compounds where attention concentrates. That reinforces Spotify’s position as the primary discovery engine in music.
Behavioral switching costs: Playlists, follows, listening history, and algorithmic tuning create friction. The subscription price is low. The time invested is not. Research firm Antenna estimates Spotify’s net churn at around 2%, with nearly 90% of audio users sticking to a single platform.
This is not a wide moat built on exclusive content. It is a narrow moat built on habit, data, and distribution scale.
AI can make the music, but Spotify is where it breaks into the culture. As long as Spotify owns the charts and the discovery, they own the power over creators. A simple algorithm push can make or break an artist, a la Netflix.
Scale alone brings new business opportunities. For example, Spotify just partnered with bookshop.org, allowing listeners in the US and the UK to buy physical books in one click from the app. It’s an example of a strategy trying to meet customers where they are and cater to their extra needs, whatever they might be.
YouTube remains the primary long-term challenger. While Spotify is the king of audio, Alphabet’s video giant owns the world’s attention. YouTube currently boasts over 2.7 billion MAUs. This scale is more than 3.5x larger than Spotify’s user base, giving YouTube an almost unfair funnel for its music services.
YouTube Music and Premium crossed 125 million subscribers in March 2025, up from 100 million a year prior. YouTube has been adding ~2 million paid subs per month on average, essentially matching Spotify’s pace. The paid subscriber base is likely close to 145 million by now, roughly half of Spotify’s Premium subs.
Alphabet is increasingly pushing its “unified content” bundle, where $13.99/month removes ads from the world’s largest video platform while simultaneously providing its music streaming service.
As YouTube Premium’s subscriber base rises, it creates a default subscription that could eat Spotify’s lunch. For a user already paying for ad-free YouTube and getting Music as a bonus, an extra $12.99/month for Spotify becomes a redundant “music tax.” YouTube Music also leverages a decade of video watch history to inform its recommendations—implicit data that Spotify’s “likes” and “saves” struggle to match. As Gen Z increasingly treats YouTube as their primary discovery engine (serving both video and audio), Spotify’s narrow moat will depend on its ability to prove that its standalone experience is worth the extra cost of a separate subscription.
Can Spotify turn cultural relevance into economic power? Can it raise ARPU without damaging the user experience? Can it defend its role as the primary music discovery engine as YouTube bundles music into a broader ecosystem?
Spotify now has the scale, data, and cash flow to execute. Yet audio carries structural limits that may cap ARPU expansion. The next phase likely requires new monetization layers beyond the current model.
Investor Day in May should provide clearer signals on how management intends to translate that foundation into sustained operating leverage.
That’s it for today!
Stay healthy and invest on!
Thanks to Fiscal.ai for being our official data partner. Create your own charts and pull key metrics from 50,000+ companies directly on Fiscal.ai. Start an account for free and save 15% on paid plans with this link.
Disclosure: I own AAPL, AMZN, GOOG, and META in App Economy Portfolio. I share my ratings (BUY, SELL, or HOLD) with members.
Author's Note (Bertrand here 👋🏼): The views and opinions expressed in this newsletter are solely my own and should not be considered financial advice or any other organization's views.
2026-02-10 21:03:43
Welcome to the Premium edition of How They Make Money.
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While the Seahawks and Patriots battled on the turf on Sunday, the real heavy-hitting happened in the ad breaks.
Anthropic decided to go for the jugular with a series of Super Bowl spots mocking OpenAI’s pivot toward a subsidized, ad-supported ChatGPT. Sam Altman fired back on X, calling the ads "clearly dishonest," and labeling Anthropic’s approach as "expensive products for rich people." The era of ad-free AI has become a marketing battleground for users and talent.
While AI labs fight for the soul of the software, the hardware world is fighting for the silicon to run it. Memory suppliers are prioritizing High-Bandwidth Memory (HBM) for AI data centers, leading to a memory crunch.
That brings us to the companies most exposed to the shortage. There’s a quiet reshuffling of power across consumer electronics, semiconductors, and platform economics.
Today at a glance:
🎮 Sony: Hardware Retreat
📲 Qualcomm: Memory Wall
☁️ Arm: Cloud AI Engine Ignites
Sony delivered a record-high operating profit for the holiday quarter (Q3 of the fiscal year ending in March), even as hardware sales for its flagship gaming console began to soften.
Sales were up just 1% Y/Y to ¥3.71 trillion (¥44 billion beat), which is roughly $23.5 billion. Operating margin improved to 14% from 12% a year ago.
The PlayStation 5 is entering the mature phase of its life cycle. Sony shipped 8 million units this quarter, a 16% drop from the 9.5 million shipped a year ago. The console has sold a cumulative total of 92 million units.
While hardware units linger, record-high software revenue on the PlayStation Store and a 13% jump in network services revenue boosted the gaming division’s operating profit, which surged 19% Y/Y.
Digital downloads and subscriptions are the main drivers here. Ghost of Yōtei was a massive catalyst, selling 3.3 million copies in its first month and outpacing the early sales of its predecessor, Ghost of Tsushima. PlayStation Network (PSN) Monthly Active Users rose 2% Y/Y to 132 million, which includes players on PS4 and PC.
The global shortage of DRAM (memory chips), driven by investments in AI and data centers, is increasing manufacturing costs. Contract prices are projected to rise 90% to 95% this quarter.
CFO Lin Tao assured investors that Sony has secured the “minimum volume required” to mitigate the crunch. She has signaled an intentional extension of the PS5 life cycle, describing the console as being only at its “midpoint.” This aligns with rumors of a delay of the PlayStation 6, possibly into 2028 or 2029, to avoid launching at a prohibitively high retail price.
While supply is secure, higher costs will weigh on hardware margins. Sony plans to absorb these costs by leaning on its installed base of PS5 owners to buy more software and subscriptions. The company is pivoting toward a services-first model.
Revenue in the Imaging & Sensing Solutions (I&SS) segment jumped 21%. This was largely driven by strong demand for high-end sensors in flagship smartphones, including the popular iPhone 17 we discussed here.
The recent pivot goes beyond the gaming segment. The company’s long-term strategy is to continue exiting low-margin manufacturing.
📺 Bravia-TCL deal: In a move that signals the end of an era, Sony is spinning off its TV business into a joint venture with TCL. The company will hold a 51% controlling stake, while Sony retains 49%. Sony will provide the “brains” (image processing and brand prestige), while TCL provides the “brawn” (manufacturing scale and supply chain efficiency). This move aims to turn the perennially struggling TV division (Entertainment, Technology & Services) into a stable, profitable entity.
🐶 Owning the IP: Sony is doubling down on content ownership. It recently increased its stake in Peanuts Holdings (Snoopy) to 80%, contributing a ¥45 billion gain to its forecast. By owning the IP, Sony ensures its music and film divisions remain essential to platforms like Netflix and Spotify.
💰 Financial streamlining: The partial spin-off of Sony Financial Group is now in effect. This allows Sony to focus its capital and attention entirely on its identity as a “Creative Entertainment Company.”
🔮 Looking forward: Sony raised its full-year operating profit forecast by 8% to ¥1.54 trillion (¥0.11 billion raise). The company may be moving fewer hardware units, but the unit economics are better than ever.